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Communication-Efficient Distributed Mining of Association Rules

Summary: New communication-efficient distributed algorithms for mining association rules in share-nothing, partitioned data. Robust to skew and imbalanced partitions, with theoretical and empirical results guiding implementation in diverse peer-to-peer-like environments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3292
Venue
SIGMOD
Year
2001
Pagerank
-
Overall Rank
13,817 | 3.88%
DOI
-

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Rank Citing Paper Year Venue Pagerank
8,040 Distributed Threshold Querying of General Functions by a Difference of Monotonic Representation 2011 VLDB 4.600049e-05
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